#SoftRobotics: #SoftActuators, #Simulators

Posted on April 27th, 2015

The meeting consisted of a presentation on commercial applications of soft grippers by Joshua Lessing @SoftRobotics followed by a panel discussion concentrating on the uses and limitations of computer simulation in the design of soft robots.

Joshua first talked about how their research, lead by George Whiteside, evolved from microfluidics (chips for device control driven by small tubes filled with fluid) to soft robotics (fluid pressure on anisotropic – directionally biased – materials to create controlled movement).

He talked about tradeoffs for different types of robotic grippers (a.k.a. end-effectors) used in manufacturing. Traditional robots offer high precision/resolution in repetitive tasks with advantages of speed and longevity but at a high price. But there are many industrial tasks done by humans since the operation does not include precise positioning of materials and the task has a lower break-even price point for automation. Soft robots could economically automation many of these tasks.

To illustrate this, Joshua described many competing end-effectors using in conjunction with mechanical arms. These solutions vary along the axes of precision, dexterity, specificity, and price. The methods include

Matthew Borgatti, the founder of Super-Releaser, a soft robotics company

Paul Grossinger, a New York entrepreneur, angel investor, and early-stage venture capitalist.

Panel Moderator: Simone Braunstein, CEO Stone Brook Robotics, LLC.

The panel talked about many aspects in the creation of soft robots, but focused on the use of computer simulation to speed the design process. One of the panelist, Jonathan Hiller, is the author of VoxCad, simulation software for the behavior of flexible objects in response to heat and pressure. The panelist agreed that there were severe limitations on the predictive capabilities of most 3-d simulation software as the non-linear reshaping of materials is difficult to accurately capture in all but the most expensive (and hard to use) packages. This means that much of the experimentation is done by prototyping systems and learning the characteristics of specific alternative materials. Matthew, for instance, has concentrated his energies on methods to rapidly modify his prototypes to quickly optimize his designs.

Paul also talked about how Johns Hopkins University has worked to create an environment that is supportive and financially-friendly to startups producing biomedical products.